The invention relates generally to the field of image registration, and more particularly to a method and system for efficiently registering images obtained via a plurality of imaging modalities.
Image registration refers to the process of finding a correspondence between the contents of two or more images. In particular, image registration refers to a process of finding a geometric transform that non-ambiguously links locations and orientations of objects or parts of objects in different images.
Image registration finds wide application in medical imaging, video motion analysis, remote sensing, security and surveillance applications. In the field of medical imaging, a patient is generally subjected to numerous scans over a number of imaging sessions. These scanned images (such as, for example, of a body part) may be obtained either temporally from the same imaging modality or system or may be captured via different imaging modalities, such as, for example, X-ray imaging systems, magnetic resonance (MR) imaging systems, computed tomography (CT) imaging systems, ultrasound imaging systems, positron emission tomography (PET) imaging systems and so forth. For example, PET imaging systems and single photon emission computed tomography (SPECT) imaging systems may be used to obtain functional body images which provide physiological information, while CT imaging systems and MR imaging systems may be used to acquire structural images of the body which provide anatomic maps of the body.
As will be appreciated by those skilled in the art, the use of different imaging modalities generates image data sets with complementary information. Hardware based registration techniques are typically useful for performing multi-modality imaging of static structures. However, for the imaging of dynamic structures, such as the heart, software based registration is additionally required to ensure a quality match. For example, in the diagnosis of cardio-vascular diseases for a patient, it may be necessary to jointly visualize and correlate coronary vasculature obtained from a CT imaging system with functional information obtained from a PET/SPECT imaging system. However, the image acquisition of dynamic structures using different modalities often has different scan durations and scan phases thereby, producing dissimilar information content. Further, large field-of-view (FOV) differences and varying resolutions between different imaging modalities may prevent the accurate correlation of these images resulting in inaccurate diagnosis of patient information.
It would be desirable to develop a technique for efficiently and accurately registering images obtained via a plurality of imaging modalities. In addition, it would be desirable to jointly visualize image data sets obtained from different imaging modalities by reliably coalescing the image data sets, to facilitate the generation of a composite, overlapping image that may include additional clinical information, which may not be apparent in each of the individual image data sets.